keras
https://github.com/keras-team/keras
Python
Deep Learning for humans
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- Issues
- TF+XLA+Mixed Precision: Keras fails to compute gradients
- Torch-cuda backend fails to recover after assertion failed
- pytorch backend lstm very +10x slow (maybe batch size with pytorch backend has different semantics than the traditional Keras semantics?)
- LSTM layer doesn't learn with TextVectorization output (padding ?)
- Feature Extraction Losses
- Integrating Hyperparameters tuning into the keras.io example classification_with_grn_and vsn.py script
- Use Multi GPU(Mirrored Strategy) training with XLA and AMP(Mixed Precision)
- RFC: Parameter Server Training for the Keras JAX backend (Keras-JAX-PST)
- add RandomApply and RandomChoice
- Bug in functional model
- Docs
- Python not yet supported